This document summarizes a research study that examined factors influencing consumer buying behavior for DTH (direct-to-home) brands in Jodhpur City, India. The researchers conducted a survey of 500 consumers to identify key variables that impact consumer purchasing of DTH services. Multiple regression analysis identified 10 variables that influence consumer buying behavior for DTH brands, including awareness of products, picture quality, expectations, preference for bestselling brands, interest in new brands, searching for good packages, carefully selecting providers based on value, spending habits, brand loyalty, and changing providers regularly. The study aims to understand how celebrity endorsements directly or indirectly impact consumer buying behavior for DTH services in Jodhpur City.

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Measuring Factors of Consumer Buying Behaviour For Dth
Brand in Jodhpur City
Dr. M. L. VASITA
Associate Professor, Department of Business Administration, University of Rajasthan,
Jaipur, Rajasthan-India
&
RANI GEHLOT
Research Scholar, Department of Business Administration, University of Rajasthan,
Jaipur, Rajasthan-India
Abstract
Celebrity endorsement is the important factor, which grabs the customer’s attention
towards the product and services. The buying behaviour of a customer is strongly
influenced by the efforts made by the advertisers to build brand loyalty. Attention
seeking ads and the use of celebrities in ads are very popular and successful as it gives
the wanted results to the companies. The proposed research will mainly shed light on
celebrity’s impact, whether directly or indirectly, on consumer buying behaviour in
relation to selected DTH service providers. By using multiple regression method 10
variables that has an impact over consumer buying behaviour for DTH brand in
Jodhpur city were identified.
INTRODUCTION
Celebrity branding or celebrity endorsement is a form of advertising campaign or
marketing strategy used by brands, companies, or a non-profit organization which
involves celebrities or a well-known person using their social status or their fame to
help promote a product, service or even raise awareness on environmental or social
matters. Marketers use celebrity endorsers in hopes that the positive images of the
celebrity endorser of the brand will also be passed on to the products or the brand
image associated with the celebrities. Celebrity endorsement is usually commonly
used by fashion or beauty brands, but a non-profit organization relies on celebrities as
well, as celebrities have mass communication skills which can attract people's
attention and is helpful in reaching a wider audience to raise their awareness towards
a certain organization or an issue, thus making celebrities effective fundraisers1
.
Endorsements by celebrities have started since a long time. The very fact that their
use has continued for so long is proof enough of its immense advantages, but they
have several disadvantages too. When it comes to celebrity endorsement, the first
brand that comes to the Indian mind is that of Lux, the Beauty Bar of the Stars. Since
its inception, Lux the brand has grown positioning itself thus. However, recently Lux
has tried to change its positioning from being a woman’s soap to being soap for men
as well. Sticking to its strategy of using celebrities to appeal to its target audience, this
time around it has used Shah Rukh Khan to endorse Lux. But this time the response
has been confusing. One of the first sports endorsements in India was when Farokh
Engineer became the first Indian Crickets to model for Brylcream The Indian cricket
teams now earns roughly Rs. 100 crore through endorsements. There was a spurt of
advertising, featuring stars like tabassum (Prestige Pressure cookers), Jalal Agha (Pan

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Parag), Kapil Dev (Palmolive Shaving cream) and Sunil Gavaskar (Dinesh Sutings)2
.
The proposed research will mainly shed light on celebrity’s impact, whether directly
or indirectly, on consumer buying behaviour in relation to selected DTH service
providers at Jodhpur city.
REVIEWS OF LITERATURE
Spiteri (2020)3
conducted an advances research into impulse buying by examining
how this behaviour is reinforced/curtailed, highlighting the primary role of the
post‐purchase experience in encouraging future impulse buying behaviour. Extant
research emphasizes the role of the purchase experience, that is, psychological
benefits attained from the impulse purchase experience itself, as a reinforcer of
impulse buying.
Sardana, Gupta and Sharma (2018)4
extended the growing research on the influence of
religion and spiritualism on consumer behaviour by exploring the relationship
between spirituality and religiosity (intrinsic vs. extrinsic) as well as their effects on
consumers’ purchase of Fast Moving Consumer Goods brands promoted by spiritual
leaders (spiritual brands). Results from an online survey of 238 Indian consumers
across four food product categories (honey, cheese, biscuits and cooking oil) shows
that both intrinsic and extrinsic religiosity have significant positive effects, but
spirituality has no significant effect on the purchase of spiritual brands. They discuss
the theoretical and managerial implications of these findings as well as some
limitations of their study and useful directions for future research.
Millan and Wright (2018)5
hypotheses are tested on a large‐scale sample of some
1,000+ respondents drawn in the Czech Republic. Using analysis of variance tests,
gender differences were found with regard to all but one consumer behaviour
phenomenon. No gender effect was found only regarding consumer preference for
clothing affiliation symbolism. The study contributes to the theoretical development
and empirical evidence in the field of gendered symbolic and hedonic consumption of
clothing artefacts. Its findings also suggest possible actions by fashion marketers, as
well as some interesting venues for future research.
Jaiswal & Singh(2018)6
revealed that the green buying behaviour can stimulate firms
and society in the pursuit of sustainability while balancing the demand and supply
side of the business cycle with addressing the ecological and social benefits. The
objective of this paper is to understand and test the integrative model of green buying
behaviour in the Indian and Asian context of sustainable consumption. The model is
tested by applying structural equation modeling of path analysis using the total of 410
valid responses. The discussion and implications are manifested towards sustainable
consumption in the context of emerging target markets.
Garay‐Quintero, Robayo‐Pinzon and Rojas‐Berrio(2018)7
found that the description of
a buying behaviour with significant restrictions, conditioned by the individuals’
religious affiliation or beliefs. Some habits, such as fasting and the importance of
health and image regarding both food and alcoholic beverages, are listed as well as
the type of symbolic consumption with religious community leaders teaching and
recommending customs that are consistent with their doctrine.
Khare& Sadachar (2017)8
found that past green behaviour influenced green apparel
buying behaviour. Green peer influence and green apparel knowledge had no impact
on green apparel buying behaviour. Moreover, CSII had no influence on green apparel
buying behaviour. The findings differ from earlier studies that suggest influence of

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social norms and peer group had an effect on green buying behaviour. Practical
implications of the present study are discussed
Wang, He, Sahadev and Song (2018)9
most of prior studies focus on the attitude of
products from Western developed countries. Their study intends to investigate the
effects of consumers' national identification and culture sensitivity on their perceived
risk of buying products from Eastern developing countries. Especially, this study
advances the literature by identifying the mediation effect of consumer ethnocentrism
and the moderating effect of consumer value consciousness. Taking China and India
as focal emerging economies, the consumer survey (n = 308) in the United Kingdom
produced the following results. First, U.K. consumers' national identification is
positively related to their perceived risk of buying Eastern products through consumer
ethnocentrism, whereas their cultural sensitivity has a negative relationship. Second,
the effect of consumer ethnocentrism on the perceived risk of buying Eastern products
is moderated by consumer value consciousness. Third, value consciousness also
attenuates the indirect relationships between national identification or cultural
sensitivity and perceived risk via consumer ethnocentrism.
Boccia and Sarnacchiaro (2018)10
conducted investigation through a sample size
survey. The analysis was carried out considering a representative sample of more than
300 families, selected on a functional relation to the objectives of the work in one of
the most important and representative Italian cities. This study has two main aims: to
investigate consumer preferences regarding responsible initiatives of a company; and
to develop and validate a structural equation model, in order to formalize the origins
of behaviours regarding consumer preferences towards responsible initiatives and
detect the drivers of their purchase.
Frank (2018)11
revealed that this role conflict derives, for example, from economic
demands sent by the consumer role set when a person has ethical buying intentions.
Additionally, the identification with the consumer role further amplifies this conflict.
The data indicate that consumers instead of citizens should be empowered by
marketing practitioners and policy makers, for example by reducing the perception of
stress by communicating positive outcomes referring to relevant consumer role set
members (e.g., added value for children from purchasing ethically) to stimulate
problem–focused coping.
Koen, Wentzel‐Viljoen, Blaauw (2018)12
revealed that Consumers struggled to
understand the information on labels, specifically the nutrition information table. A
lack of time or interest, price concerns and trust in labelling information also emerged
as reasons why consumers ignore the nutrition information. There is a need for
simpler food labelling, more graphics, and less complex terminology, information
overload and quantitative information. It is recommended that a standardised
front‐of‐package labelling scheme and a single health endorsement logo for South
Africa be considered. More should be done to educate consumers on utilising the
information on food labels correctly, in order for them to make healthier food choices.
Sipilä, Sundqvist and Tarkiainen (2017)13
explored that different ambivalences consist
of, what their roles are in the buying process, and how they occur under different
types of involvement conditions. A longitudinal video diary method is used in
conjunction with a multimodal analysis technique to explore not only the verbally
expressed aspects of ambivalence but also its nonverbal expression, which further
reveals differences between different types of ambivalence. The findings suggest that
cognitive ambivalence involves conflicting evaluations of utilitarian brand and
product aspects and is resolved through more effortful mechanisms, whereas
intercomponent ambivalence involves conflicting evaluations of varying utilitarian,

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hedonic, and symbolic brand and product aspects and is resolved through both more
and less effortful mechanisms. Finally, affective ambivalence involves conflicting
anticipations about the outcome of the buying process but is not resolved through
similarly clear mechanisms. As the key outcome of the exploration, propositions and a
synthesising framework about the different types of ambivalence in the buying
process are developed for future research. This paper hence contributes to the
ambivalence literature and offers managerial implications especially for marketers of
multifaceted and high‐involvement products.
Torres‐Ruiz, Vega‐Zamora, and Parras‐Rosa(2018)14
revealed that explanatory
models of consumer behaviour can be used to steer decision‐making in the complex
task of designing generic strategies to increase sustainable consumption. This paper
proposes an operational model which assumes that the purchase of an organic food is
a complex process that can be broken down into phases. It is applied to a concrete
case – organic olive oil in the Spanish market – quantifying each phase to determine
which ones should be acted on to increase demand. Results indicate that it is possible
to adopt the model proposed, and that the problems hindering consumption are a lack
of confidence in organic certification, not perceiving differences between organic and
conventional foods, and the perception of barriers in their purchase. Given the
context, marketing communications strategies have a key role to play. This model can
be used to analyse the specific situation of each market and propose development
strategies.
RESEARCH METHODOLOGY
Sample unit: consumers of the DTH brand of Jodhpur city are the sample units.
Sample size: 500 consumers of Jodhpur city.
Sampling Technique:In present research, the respondents were selected using
convenience sampling.
Data Source:Primary data is collected from firsthand experience and may coined as
raw data collected on source which has not been subjected to processing or any other
manipulation. The data regarding the current research is taken from 500 consumers at
Jodhpur city.
Statistical tools and Techniques: the data is analysed using the multiple regression
test by SPSS-19 software.

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DATA ANALYSIS
The demographic profiles of the respondents are as under:
Table-1: Demographical profile
Age Frequency Percent Gender Frequency Percent
18-25 325 65.0 Male 253 50.6
26-35 110 22.0 Female 247 48.4
36-45 44 8.8 Education Frequency Percent
above 45 21 4.2 up to XII 122 24.4
Occupation Frequency Percent Graduate 164 32.8
Job 228 45.6 Post Graduate 163 32.6
Student 144 28.8 Professional 51 10.2
Service 80 16.0 DTH used Frequency Percent
Business 48 9.6 DD Free Dish 37 7.4
Income level Frequency Percent Dish TV 148 29.6
below 10,000 250 50.0 Tata Sky 147 29.4
10,000-25,000 115 23.0 Airtel digital TV 139 27.8
25000-50000 108 21.6 Sun Direct 29 5.8
Above 50000 27 5.4
To measure the Celebrity impact on the consumer’s buying behaviour regarding DTH
brand in Jodhpur city following hypothesis is developed:
H1= Variables of Celebrity have significant impact on the consumer’s buying
behaviour regarding DTH brand in Jodhpur city
To analyse the above hypothesis the multiple regression analysis is conducted with
SPSS-19 software and the results are as under:
Table-2: Multiple Regression results
Descriptive Statistics
Variable SPSS code Mean Std.
Deviation
N
Awareness about the product will affect your purchase
decision?
conBuy_beh
3.9280 1.18559 500
I make special effort to choose the DTH that provide picture
quality the best quality.
conBuy_beh_1
3.8960 1.22318 500
My standard and expectations for DTH service is very high. conBuy_beh_2 3.5900 1.11732 500
The more expensive DTH brands of goods are usually my
choice.
conBuy_beh_3
2.8700 1.07676 500
I prefer buying the bestselling DTH brands for My
entertainment.
conBuy_beh_4
3.3840 1.16243 500
I wish to Try and use the DTH brand that are new and look
good once.
conBuy_beh_5
2.8240 1.09335 500
When I hear of a new Pack for channels, I want to take
advantage of the first opportunity to find out more about it.
conBuy_beh_6
3.2420 1.21424 500
Searching for good package is one of the most enjoyable
activities for me.
conBuy_beh_7
3.5300 1.07676 500
I always Look carefully to find the best DTH service with best
pack for the value of money.
conBuy_beh_8
3.4980 1.24624 500

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Often I make careless selection for DTH package purchases, I
later wish I had not bought them
conBuy_beh_9
2.6500 1.21427 500
I carefully watch how much I spend on DTH services. conBuy_beh_10 3.6900 1.06215 500
I have favorite DTH service and I regularly use the same
operator and buy same pack again and again.
conBuy_beh_11
3.7240 1.04019 500
I regularly change the DTH operator/ pack. conBuy_beh_12 2.1860 1.07597 500
I go to the same Pack each time; I shop for DTH provider after
each year period.
conBuy_beh_13
3.4800 1.01373 500
Correlations
conBu
y_beh
conBuy
_beh_1
conBuy
_beh_2
conBuy
_beh_3
conBuy
_beh_4
conBuy
_beh_5
conBuy
_beh_6
conBuy
_beh_7
conBuy
_beh_8
conBuy
_beh_9
conBuy
_beh_1
0
conBuy
_beh_1
1
conBuy
_beh_1
2
conBuy
_beh_1
3
Pea
rso
n
Cor
rela
tion
conBuy_b
eh
1.000 .783 .661 .307 .397 .276 .517 .666 .606 .090 .724 .631 .072 .212
conBuy_b
eh_1
.783 1.000 .753 .203 .492 .281 .503 .637 .531 .000 .651 .636 .074 .333
conBuy_b
eh_2
.661 .753 1.000 .292 .415 .335 .502 .549 .403 .201 .580 .484 .152 .393
conBuy_b
eh_3
.307 .203 .292 1.000 .501 .564 .461 .402 .259 .403 .240 .376 .382 .153
conBuy_b
eh_4
.397 .492 .415 .501 1.000 .506 .533 .650 .279 .132 .452 .391 .149 .194
conBuy_b
eh_5
.276 .281 .335 .564 .506 1.000 .610 .427 .303 .467 .262 .227 .365 .138
conBuy_b
eh_6
.517 .503 .502 .461 .533 .610 1.000 .605 .315 .208 .542 .437 .234 .316
conBuy_b
eh_7
.666 .637 .549 .402 .650 .427 .605 1.000 .488 .108 .650 .494 .209 .367
conBuy_b
eh_8
.606 .531 .403 .259 .279 .303 .315 .488 1.000 .175 .560 .443 .215 .102
conBuy_b
eh_9
.090 .000 .201 .403 .132 .467 .208 .108 .175 1.000 .088 .085 .340 -.023
conBuy_b
eh_10
.724 .651 .580 .240 .452 .262 .542 .650 .560 .088 1.000 .617 .112 .347
conBuy_b
eh_11
.631 .636 .484 .376 .391 .227 .437 .494 .443 .085 .617 1.000 .096 .419
conBuy_b
eh_12
.072 .074 .152 .382 .149 .365 .234 .209 .215 .340 .112 .096 1.000 .228
conBuy_b
eh_13
.212 .333 .393 .153 .194 .138 .316 .367 .102 -.023 .347 .419 .228 1.000
Sig.
(1-
tail
ed)
conBuy_b
eh
. .000 .000 .000 .000 .000 .000 .000 .000 .023 .000 .000 .054 .000
conBuy_b
eh_1
.000 . .000 .000 .000 .000 .000 .000 .000 .498 .000 .000 .049 .000
conBuy_b
eh_2
.000 .000 . .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
conBuy_b
eh_3
.000 .000 .000 . .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
conBuy_b
eh_4
.000 .000 .000 .000 . .000 .000 .000 .000 .002 .000 .000 .000 .000
conBuy_b
eh_5
.000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 .000 .000 .001
conBuy_b
eh_6
.000 .000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 .000 .000
conBuy_b
eh_7
.000 .000 .000 .000 .000 .000 .000 . .000 .008 .000 .000 .000 .000
conBuy_b
eh_8
.000 .000 .000 .000 .000 .000 .000 .000 . .000 .000 .000 .000 .011
conBuy_b
eh_9
.023 .498 .000 .000 .002 .000 .000 .008 .000 . .024 .028 .000 .306
conBuy_b
eh_10
.000 .000 .000 .000 .000 .000 .000 .000 .000 .024 . .000 .006 .000
conBuy_b
eh_11
.000 .000 .000 .000 .000 .000 .000 .000 .000 .028 .000 . .016 .000
conBuy_b
eh_12
.054 .049 .000 .000 .000 .000 .000 .000 .000 .000 .006 .016 . .000
conBuy_b
eh_13
.000 .000 .000 .000 .000 .001 .000 .000 .011 .306 .000 .000 .000 .
N 500 500 500 500 500 500 500 500 500 500 500 500 500 500

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Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
10 .879j .772 .768 .57159 .003 6.751 1 489 .010
ANOVAa
Model Sum of Squares df Mean Square F Sig.
10
Regression 541.642 10 54.164 165.781 .000k
Residual 159.766 489 .327
Total 701.408 499
k. Predictors: (Constant), conBuy_beh_1, conBuy_beh_10, conBuy_beh_8, conBuy_beh_7, conBuy_beh_13, conBuy_beh_4,
conBuy_beh_3, conBuy_beh_11, conBuy_beh_2, conBuy_beh_12
Coefficientsa
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig. Correlations Collinearity
Statistics
B Std.
Error
Beta Zero-
order
Partial Part Toleran
ce
VIF
10
(Constant) .365 .126 2.897 .004
conBuy_beh_1 .362 .042 .373 8.673 .000 .783 .365 .187 .252 3.974
conBuy_beh_10 .263 .039 .235 6.761 .000 .724 .292 .146 .385 2.601
conBuy_beh_8 .098 .028 .103 3.545 .000 .606 .158 .077 .555 1.802
conBuy_beh_7 .278 .040 .252 6.946 .000 .666 .300 .150 .353 2.831
conBuy_beh_13 -.192 .031 -.164 -6.219 .000 .212 -.271 -.134 .672 1.489
conBuy_beh_4 -.208 .032 -.204 -6.481 .000 .397 -.281 -.140 .468 2.136
conBuy_beh_3 .124 .032 .113 3.835 .000 .307 .171 .083 .538 1.860
conBuy_beh_11 .146 .038 .128 3.849 .000 .631 .171 .083 .419 2.388
conBuy_beh_2 .136 .038 .128 3.614 .000 .661 .161 .078 .372 2.686
conBuy_beh_12 -.070 .027 -.064 -2.598 .010 .072 -.117 -.056 .771 1.298
a. Dependent Variable: conBuy_beh
CONCLUSION
The results of the study revealed 10 variables that has impact over consumer buying
behaviour for DTH brand in Jodhpur city including they make special effort to choose
the DTH that provide picture quality the best quality, The more expensive DTH
brands of goods are usually my choice, I prefer buying the bestselling DTH brands for
My entertainment, Searching for good package is one of the most enjoyable activities
for me, I always Look carefully to find the best DTH service with best pack for the
value of money, I carefully watch how much I spend on DTH services, I have favorite
DTH service and I regularly use the same operator and buy same pack again and
again, I regularly change the DTH operator/ pack and I go to the same Pack each
time; I shop for DTH provider after each year period.
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